The “Threads” link came much later; “Comments” link on your profile is there from a long time ago, or maybe since beginning. Now it’s a redirect to “Threads”.
I personally encountered that problem with browser use and I developed a listener on top that gets triggered when there’s a captcha, so it just switch off chrome headless so the user can solve it before proceeding.
Sure, Opus is next level than Sonnet, but it still doesn't free OP from these handcuffs - It is reading the code, understanding it and making a mental model that's way more labour intensive.
The OP's problem was treating the situation as two extremes: Either write everything myself, or defer entirely to the AI and be forced to read it later.
I was trying to explain that this isn't how successful engineers use AI. There is a way to understand the code and what the AI is doing as you're working with it.
Writing a spec, submitting it to the AI (a second-tier model at that) and then being disappointed when it didn't do exactly what you wanted in a perfect way is a tired argument.
Is doing that faster than just writing it by hand? Remember to include the time you need to review the code afterwards. The research so far says it isn't faster. Yet people keep doubling down on it and thinking winning an Internet argument is going to matter when it hits the fan in the near future.
> that would be >900k tokens written to cache all at once
Probably that's why I hit my weekly limits 3-4 days ago, and was scheduled to reset later today. I just checked, and they are already reset.
Not sure if it's already done, shouldn't there be a check somewhere to alert on if an outrageous number of tokens are getting written, then it's not right ?
How much time to verify and validate that large corpus of code that they generated? Not including back and forth to get rid of hallucinations and other mistakes.
How does the code look? I am curious if there is proper usage of abstractions, or is logic just kind of all over the place?
Some part of me feels like LLM generated code is great if one cares about the solution, but leaves a lot to be desired if one actually cares about code quality. Then again, maybe I am just bad as using LLMs -- I prefer the chat over lettings LLMs do the work for me.
> It's very nerve-racking for people who like to have a deep understanding of everything they ship.
A deep domain knowledge of your industry and your business (company/org) makes you very valuable in your team and your company. I've seen people survive layoffs and other cost-cutting cycles just because they possessed immense knowledge compared to those who did not.
I suspect that as the value a company provides is more than its code, then increasing code churn does not lead to an equivalent increase in revenue. Even for a tech company, a business' concept, connections, knowledge, assets, non-coding staff, etc.. are a significant value and increasing code doesn't increase the throughput of that value. For non-tech companies code is the grease in the gears, not the gears themselves.
Facebook now has 'Audience', which is quite analogous to 'Circles'
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